{
 "cells": [
  {
   "cell_type": "markdown",
   "metadata": {
    "colab_type": "text",
    "id": "view-in-github"
   },
   "source": [
    "<a href=\"https://colab.research.google.com/github/oughtinc/ergo/blob/master/notebooks/quickstart.ipynb\" target=\"_parent\"><img src=\"https://colab.research.google.com/assets/colab-badge.svg\" alt=\"Open In Colab\"/></a>"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {
    "colab_type": "text",
    "id": "maTou6hocLTE"
   },
   "source": [
    "# Setup"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 3,
   "metadata": {
    "colab": {
     "base_uri": "https://localhost:8080/",
     "height": 0
    },
    "colab_type": "code",
    "id": "lyp6fM-Zb4ly",
    "outputId": "64f0c3c6-072e-4f5e-fec3-99ec590ba331"
   },
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "  Installing build dependencies ... \u001b[?25l\u001b[?25hdone\n",
      "  Getting requirements to build wheel ... \u001b[?25l\u001b[?25hdone\n",
      "    Preparing wheel metadata ... \u001b[?25l\u001b[?25hdone\n",
      "  Building wheel for ergo (PEP 517) ... \u001b[?25l\u001b[?25hdone\n"
     ]
    }
   ],
   "source": [
    "!pip install --progress-bar off --quiet poetry\n",
    "!pip install --progress-bar off --quiet git+https://github.com/oughtinc/ergo.git"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {
    "colab_type": "text",
    "id": "CWGrht6fc_GF"
   },
   "source": [
    "# Load questions"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "metadata": {
    "colab": {},
    "colab_type": "code",
    "id": "KEMFjKkQcPyD"
   },
   "outputs": [],
   "source": [
    "import ergo\n",
    "import seaborn"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {
    "colab_type": "text",
    "id": "r0BkLCoNchJn"
   },
   "source": [
    "Log into Metaculus:"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "metadata": {
    "colab": {},
    "colab_type": "code",
    "id": "AHvdB2Zzcj7v"
   },
   "outputs": [],
   "source": [
    "metaculus = ergo.Metaculus()"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {
    "colab_type": "text",
    "id": "5fMzhL7jc6dX"
   },
   "source": [
    "Load some questions:"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "metadata": {
    "colab": {},
    "colab_type": "code",
    "id": "1HqmElqReZm5"
   },
   "outputs": [],
   "source": [
    "q_infections = metaculus.get_question(3529, name=\"Covid-19 infections in 2020\")\n",
    "q_ratio = metaculus.get_question(3755, name=\"Covid-19 ratio of fatalities to infections\")"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {
    "colab_type": "text",
    "id": "IrKjc3zmehYx"
   },
   "source": [
    "Build a model:"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 8,
   "metadata": {
    "colab": {
     "base_uri": "https://localhost:8080/",
     "height": 34
    },
    "colab_type": "code",
    "id": "sZirbidReiR2",
    "outputId": "3fd66857-aa69-4361-f251-3b4a3bdb5b58"
   },
   "outputs": [
    {
     "name": "stderr",
     "output_type": "stream",
     "text": [
      "100%|██████████| 5000/5000 [00:05<00:00, 972.26it/s] \n"
     ]
    }
   ],
   "source": [
    "def model():\n",
    "    infections = q_infections.sample_community()\n",
    "    ratio = q_ratio.sample_community()\n",
    "    deaths = infections * ratio\n",
    "    ergo.tag(deaths, \"Covid-19 deaths in 2020\")\n",
    "\n",
    "samples = ergo.run(model, num_samples=5000)"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {
    "colab_type": "text",
    "id": "9rrA73ZMeqme"
   },
   "source": [
    "Show samples:"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 11,
   "metadata": {
    "colab": {
     "base_uri": "https://localhost:8080/",
     "height": 307
    },
    "colab_type": "code",
    "id": "ZVxZVKkbesEY",
    "outputId": "65eb6943-1cde-4e73-b2fe-fd83cee167e4"
   },
   "outputs": [
    {
     "data": {
      "text/plain": [
       "<matplotlib.axes._subplots.AxesSubplot at 0x7f2fe12cd588>"
      ]
     },
     "execution_count": 11,
     "metadata": {
      "tags": []
     },
     "output_type": "execute_result"
    },
    {
     "data": {
      "image/png": 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\n",
      "text/plain": [
       "<Figure size 432x288 with 1 Axes>"
      ]
     },
     "metadata": {
      "needs_background": "light",
      "tags": []
     },
     "output_type": "display_data"
    }
   ],
   "source": [
    "seaborn.distplot(samples[\"Covid-19 deaths in 2020\"])"
   ]
  }
 ],
 "metadata": {
  "colab": {
   "authorship_tag": "ABX9TyMnIWXH0zoPqedb0goMNGc0",
   "collapsed_sections": [
    "maTou6hocLTE"
   ],
   "include_colab_link": true,
   "name": "Quickstart",
   "provenance": []
  },
  "kernelspec": {
   "display_name": "Python 3",
   "language": "python",
   "name": "python3"
  },
  "language_info": {
   "codemirror_mode": {
    "name": "ipython",
    "version": 3
   },
   "file_extension": ".py",
   "mimetype": "text/x-python",
   "name": "python",
   "nbconvert_exporter": "python",
   "pygments_lexer": "ipython3",
   "version": "3.6.8"
  }
 },
 "nbformat": 4,
 "nbformat_minor": 4
}